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Harnessing Big Data: Uncovering New Antimicrobials

A new approach has been developed by researchers to identify potential antimicrobial drugs from bacterial datasets, offering insights into alternative solutions to conventional antibiotics.

A recent study published in eLife introduces a novel strategy for uncovering antimicrobial lysins—enzymes produced by phages during infection— with therapeutic benefits. The study highlights the discovery of two promising lysins, PHAb10 and PHAb11, and aims to provide useful information for microbiologists in further research.

The escalating threat of antibiotic resistance, where disease-causing microorganisms evolve to withstand existing treatments, poses a significant global health challenge. The misuse of antimicrobial agents in various sectors has been identified as a key factor driving the proliferation of resistance.

Lysins, derived from bacteriophages that infect bacteria, offer antimicrobial effects and are considered a viable alternative to antibiotics due to their lower risk of resistance and unique mode of action. Lead author Li Zhang, a PhD candidate, emphasizes the importance of lysins as potential treatments for infections, despite the limited availability of phage genome data.

Past research on lysins has associated their antimicrobial properties with internal peptides, which led Zhang and the team to explore bacterial proteome datasets for new lysins with antimicrobial activity. By utilizing the proteome database of the bacterium Acinetobacter baumannii, the researchers were able to identify five new lysins, notably PHAb7-11, with PHAb10 and PHAb11 showing the most promise.

Further evaluations involved synthesizing the gene-coding sequences for the lysins and testing their antimicrobial efficacy against different bacterial species, demonstrating potent antibacterial activity even at low concentrations.

The study also assessed the antibacterial performance of PHAb10 and PHAb11 across various conditions, showcasing robust activity against bacteria in different growth phases, including those resistant to traditional antibiotics. Additionally, the researchers observed the thermostability of PHAb10, elucidating its structural changes under heat stress, a feature crucial for its potential therapeutic use.

The team’s findings underscore the potential of leveraging big data, including bacterial genomes and proteomes, in combating antibiotic resistance. By utilizing a screening strategy, the researchers identified highly thermostable lysins with broad-spectrum antimicrobial properties in PHAb10 and PHAb11, warranting further investigation for their therapeutic applications.

The researchers highlight the importance of conducting additional tests, such as live/dead assays, to strengthen the credibility of their findings and better understand the mechanisms of bacterial eradication by lysins.

Senior author Hang Yang stresses the significance of daily updated big data in the fight against antibiotic resistance and underscores the importance of the team’s approach in identifying potential therapeutic lysins. If validated in subsequent studies, PHAb10 and PHAb11 could emerge as promising candidates for treating bacterial infections.